Tue, 11 May 2021

New package GreedyEPL with initial version 1.1
Package: GreedyEPL
Title: Greedy Expected Posterior Loss
Version: 1.1
Date: 2021-05-11
Authors@R: person(given = "Riccardo", family = "Rastelli", role = c("aut", "cre"), email = "riccardoras@gmail.com")
Description: Summarises a collection of partitions into a single optimal partition. The objective function is the expected posterior loss, and the minimisation is performed through a greedy algorithm described in Rastelli, R. and Friel, N. (2017) "Optimal Bayesian estimators for latent variable cluster models" <DOI:10.1007/s11222-017-9786-y>.
License: GPL-3
Imports: Rcpp (>= 0.12.10)
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
Packaged: 2021-05-11 17:37:23 UTC; riccardo
Author: Riccardo Rastelli [aut, cre]
Maintainer: Riccardo Rastelli <riccardoras@gmail.com>
Repository: CRAN
Date/Publication: 2021-05-12 01:02:11 UTC

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Package WienR updated to version 0.2-0 with previous version 0.1-9 dated 2021-05-07

Title: Derivatives of the Diffusion Density and Cumulative Distribution Function
Description: Calculates the partial derivative of the first-passage time diffusion probability density function (PDF) and cumulative distribution function (CDF) with respect to the first-passage time t (only for PDF), the upper barrier a, the drift rate v, the relative starting point w, the non-decision time t0, the inter-trial variability of the drift rate sv, the inter-trial variability of the rel. starting point sw, and the inter-trial variability of the non-decision time st0. In addition the PDF and CDF themselves are also provided. Most calculations are done on the logarithmic scale to make it more stable. Since the PDF, CDF, and their derivatives are represented as infinite series, we give the user the option to control the approximation errors with the argument 'precision'. For the numerical integration we used the C library cubature by Johnson, S. G. (2005-2013) <https://github.com/stevengj/cubature>. Numerical integration is required whenever sv, sw, and/or st0 is not zero. Note that numerical integration reduces speed of the computation and the precision cannot be guaranteed anymore. Therefore, whenever numerical integration is used an estimate of the approximation error is provided in the output list.
Author: Raphael Hartmann [aut, cre], Karl C. Klauer [cph, aut, ctb, ths], Steven G. Johnson [ctb], Jean M. Linhart [ctb], Brian Gough [ctb], Gerard Jungman [ctb], Rudolf Schuerer [ctb], Przemyslaw Sliwa [ctb], Jason H. Stover [ctb]
Maintainer: Raphael Hartmann <raphael.hartmann@protonmail.com>

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Package smoots updated to version 1.1.0 with previous version 1.0.1 dated 2019-12-02

Title: Nonparametric Estimation of the Trend and Its Derivatives in TS
Description: The nonparametric trend and its derivatives in equidistant time series (TS) with short-memory stationary errors can be estimated. The estimation is conducted via local polynomial regression using an automatically selected bandwidth obtained by a built-in iterative plug-in algorithm or a bandwidth fixed by the user. A Nadaraya-Watson kernel smoother is also built-in as a comparison. With version 1.1.0, a linearity test for the trend function, forecasting methods and backtesting approaches are implemented as well. The smoothing methods of the package are described in Feng, Y., Gries, T., and Fritz, M. (2020) <doi:10.1080/10485252.2020.1759598>.
Author: Yuanhua Feng [aut] (Paderborn University, Germany), Sebastian Letmathe [aut] (Paderborn University, Germany), Dominik Schulz [aut, cre] (Paderborn University, Germany), Thomas Gries [ctb] (Paderborn University, Germany), Marlon Fritz [ctb] (Paderborn University, Germany)
Maintainer: Dominik Schulz <schulzd@mail.uni-paderborn.de>

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Package oppr updated to version 1.0.3 with previous version 1.0.2 dated 2020-05-20

Title: Optimal Project Prioritization
Description: A decision support tool for prioritizing conservation projects. Prioritizations can be developed by maximizing expected feature richness, expected phylogenetic diversity, the number of features that meet persistence targets, or identifying a set of projects that meet persistence targets for minimal cost. Constraints (e.g. lock in specific actions) and feature weights can also be specified to further customize prioritizations. After defining a project prioritization problem, solutions can be obtained using exact algorithms, heuristic algorithms, or random processes. In particular, it is recommended to install the 'Gurobi' optimizer (available from <https://www.gurobi.com>) because it can identify optimal solutions very quickly. Finally, methods are provided for comparing different prioritizations and evaluating their benefits. For more information, see Hanson et al. (2019) <doi:10.1111/2041-210X.13264>.
Author: Jeffrey O Hanson [aut, cre] (<https://orcid.org/0000-0002-4716-6134>), Richard Schuster [aut] (<https://orcid.org/0000-0003-3191-7869>), Matthew Strimas-Mackey [aut] (<https://orcid.org/0000-0001-8929-7776>), Joseph R Bennett [aut] (<https://orcid.org/0000-0002-3901-9513>)
Maintainer: Jeffrey O Hanson <jeffrey.hanson@uqconnect.edu.au>

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Package kdevine updated to version 0.4.3 with previous version 0.4.2 dated 2018-12-17

Title: Multivariate Kernel Density Estimation with Vine Copulas
Description: Implements the vine copula based kernel density estimator of Nagler and Czado (2016) <doi:10.1016/j.jmva.2016.07.003>. The estimator does not suffer from the curse of dimensionality and is therefore well suited for high-dimensional applications.
Author: Thomas Nagler [aut, cre]
Maintainer: Thomas Nagler <mail@tnagler.com>

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Package FishResp updated to version 1.1.0 with previous version 1.0.3 dated 2019-03-07

Title: Analytical Tool for Aquatic Respirometry
Description: Calculates metabolic rate of fish and other aquatic organisms measured using an intermittent-flow respirometry approach. The tool is used to run a set of graphical QC tests of raw respirometry data, correct it for background respiration and chamber effect, filter and extract target values of absolute and mass-specific metabolic rate. Experimental design should include background respiration tests and measuring of one or more metabolic rate traits. The R package is ideally integrated with the pump controller 'PumpResp' and the DO meter 'SensResp' (open-source hardware by FishResp). Raw respirometry data can be also imported from 'AquaResp' (free software), 'AutoResp' ('LoligoSystems'), 'OxyView' ('PreSens'), 'Pyro Oxygen Logger' ('PyroScience') and 'Q-box Aqua' ('QubitSystems'). More information about the R package 'FishResp'is available in the publication by Morozov et al. (2019) <doi:10.1093/conphys/coz003>.
Author: Sergey Morozov [aut, cre], Scott McCairns [aut, ths], Juha Merila [ths], Federico Calboli [ctb], Jenni Prokkola [dtc], Stephen White [dtc], Daniel Montgomery [dtc], Laura Almodovar-Acevedo [dtc], Niclas Kolm [dtc], Alexander Kotrschal [dtc], Erik Gill [dtc]
Maintainer: Sergey Morozov <sergey.morozov@helsinki.fi>

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New package doconv with initial version 0.1.2
Package: doconv
Title: Document Conversion to 'PDF' or 'PNG'
Version: 0.1.2
Authors@R: c( person("David", "Gohel", role = c("aut", "cre"), email = "david.gohel@ardata.fr"), person(given = "ArData", role = "cph") )
Description: Functions to convert 'Microsoft Word' or 'Microsoft PowerPoint' documents to 'PDF' format and also for converting them into a thumbnail. In order to work, 'LibreOffice' must be installed on the machine and possibly 'python' and 'Microsoft Word'. If the latter is available, it can be used to produce PDF documents identical to the originals, otherwise, 'LibreOffice' is used.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: magick, pdftools, locatexec, rappdirs
BugReports: https://github.com/ardata-fr/doconv/issues
SystemRequirements: LibreOffice, Microsoft Word
NeedsCompilation: no
Packaged: 2021-05-11 16:07:23 UTC; davidgohel
Author: David Gohel [aut, cre], ArData [cph]
Maintainer: David Gohel <david.gohel@ardata.fr>
Repository: CRAN
Date/Publication: 2021-05-12 00:52:24 UTC

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Package diseq updated to version 0.3.1 with previous version 0.2.1 dated 2021-04-14

Title: Estimation Methods for Markets in Equilibrium and Disequilibrium
Description: Provides estimation methods for markets in equilibrium and disequilibrium. Supports the estimation of an equilibrium and four disequilibrium models with both correlated and independent shocks. Also provides post-estimation analysis tools, such as aggregation, marginal effect, and shortage calculations. The estimation methods are based on full information maximum likelihood techniques given in Maddala and Nelson (1974) <doi:10.2307/1914215>. They are implemented using the analytic derivative expressions calculated in Karapanagiotis (2020) <doi:10.2139/ssrn.3525622>. Standard errors can be estimated by adjusting for heteroscedasticity or clustering. The equilibrium estimation constitutes a case of a system of linear, simultaneous equations. Instead, the disequilibrium models replace the market-clearing condition with a non-linear, short-side rule and allow for different specifications of price dynamics.
Author: Pantelis Karapanagiotis [aut, cre] (<https://orcid.org/0000-0001-9871-1908>)
Maintainer: Pantelis Karapanagiotis <pikappa.devel@gmail.com>

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Package BootstrapQTL updated to version 1.0.5 with previous version 1.0.2 dated 2018-09-21

Title: Bootstrap cis-QTL Method that Corrects for the Winner's Curse
Description: Identifies genome-related molecular traits with significant evidence of genetic regulation and performs a bootstrap procedure to correct estimated effect sizes for over-estimation present in cis-QTL mapping studies (The "Winner's Curse"), described in Huang QQ *et al.* 2018 <doi: 10.1093/nar/gky780>.
Author: Qin Qin Huang [aut], Scott Ritchie [aut, cre]
Maintainer: Scott Ritchie <sritchie73@gmail.com>

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Package baggr updated to version 0.6.4 with previous version 0.4.0 dated 2020-02-28

Title: Bayesian Aggregate Treatment Effects
Description: Running and comparing meta-analyses of data with hierarchical Bayesian models in Stan, including convenience functions for formatting data, plotting and pooling measures specific to meta-analysis. This implements many models from Meager (2019) <doi:10.1257/app.20170299>.
Author: Witold Wiecek [cre, aut], Rachael Meager [aut], Brice Green [ctb] (predict(), loo_compare, many visuals), Trustees of Columbia University [cph] (tools/make_cc.R)
Maintainer: Witold Wiecek <witold.wiecek@gmail.com>

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Package skpr updated to version 0.66.5 with previous version 0.64.2 dated 2020-03-04

Title: Design of Experiments Suite: Generate and Evaluate Optimal Designs
Description: Generates and evaluates D, I, A, Alias, E, T, and G optimal designs. Supports generation and evaluation of blocked and split/split-split/.../N-split plot designs. Includes parametric and Monte Carlo power evaluation functions, and supports calculating power for censored responses. Provides a framework to evaluate power using functions provided in other packages or written by the user. Includes a Shiny graphical user interface that displays the underlying code used to create and evaluate the design to improve ease-of-use and make analyses more reproducible.
Author: Tyler Morgan-Wall [aut, cre], George Khoury [aut]
Maintainer: Tyler Morgan-Wall <tylermw@gmail.com>

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Package Perc updated to version 0.1.6 with previous version 0.1.5 dated 2020-04-27

Title: Using Percolation and Conductance to Find Information Flow Certainty in a Direct Network
Description: To find the certainty of dominance interactions with indirect interactions being considered.
Author: Kevin Fujii [aut], Jian Jin [aut], Jessica Vandeleest [aut, cre], Aaron Shev [aut], Brianne Beisner [aut], Brenda McCowan [aut, cph], Hsieh Fushing [aut, cph]
Maintainer: Jessica Vandeleest <vandelee@ucdavis.edu>

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Package MultinomialCI updated to version 1.2 with previous version 1.1 dated 2019-09-07

Title: Simultaneous Confidence Intervals for Multinomial Proportions According to the Method by Sison and Glaz
Description: An implementation of a method for building simultaneous confidence intervals for the probabilities of a multinomial distribution given a set of observations, proposed by Sison and Glaz in their paper: Sison, C.P and J. Glaz. Simultaneous confidence intervals and sample size determination for multinomial proportions. Journal of the American Statistical Association, 90:366-369 (1995). The method is an R translation of the SAS code implemented by May and Johnson in their paper: May, W.L. and W.D. Johnson. Constructing two-sided simultaneous confidence intervals for multinomial proportions for small counts in a large number of cells. Journal of Statistical Software 5(6) (2000). Paper and code available at <DOI:10.18637/jss.v005.i06>.
Author: Pablo J. Villacorta <pjvi@decsai.ugr.es>
Maintainer: Pablo J. Villacorta <pjvi@decsai.ugr.es>

Diff between MultinomialCI versions 1.1 dated 2019-09-07 and 1.2 dated 2021-05-11

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Package cecs updated to version 0.2.1 with previous version 0.2.0 dated 2021-04-25

Title: R Interface for the C Implementation of CEC Benchmark Functions
Description: Goal of this package is to provide access to benchmark functions defined for the Special Session and Competition on Real-Parameter Single Objective Optimization in one place. The package contains functions from following years: 2013, 2014, 2015, 2017, 2019, 2021 (<https://github.com/P-N-Suganthan>). Implementations of CEC-2013 (Y. Gonzalez-Fernandez & M. Zambrano-Bigiarini) and CEC2017 (D. Jagodziński) are taken from existed R packages. Also, the original C source code has been cleaned and reorganized for better readability.
Author: Eryk Warchulski [aut, cre], Dariusz Jagodziński [cph], Yasser Gonzalez-Fernandez [cph], Mauricio Zambrano-Bigiarini [cph]
Maintainer: Eryk Warchulski <ewarchul@gmail.com>

Diff between cecs versions 0.2.0 dated 2021-04-25 and 0.2.1 dated 2021-05-11

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Package WeMix updated to version 3.1.7 with previous version 3.1.6 dated 2020-12-08

Title: Weighted Mixed-Effects Models Using Multilevel Pseudo Maximum Likelihood Estimation
Description: Run mixed-effects models that include weights at every level. The WeMix package fits a weighted mixed model, also known as a multilevel, mixed, or hierarchical linear model (HLM). The weights could be inverse selection probabilities, such as those developed for an education survey where schools are sampled probabilistically, and then students inside of those schools are sampled probabilistically. Although mixed-effects models are already available in R, WeMix is unique in implementing methods for mixed models using weights at multiple levels. Both linear and logit models are supported. Models may have up to three levels.
Author: Emmanuel Sikali [pdr], Paul Bailey [aut, cre], Claire Kelley [aut], Trang Nguyen [aut], Huade Huo [aut], Eric Buehler [ctb], Christian Kjeldsen [ctb]
Maintainer: Paul Bailey <pbailey@air.org>

Diff between WeMix versions 3.1.6 dated 2020-12-08 and 3.1.7 dated 2021-05-11

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Package timsr updated to version 0.0.3 with previous version 0.0.2 dated 2021-05-04

Title: Easily Access timsTOF Data
Description: Access 'timsTOF' mass spectrometry data, as described <https://sso.bruker.com/auth/realms/bruker/protocol/openid-connect/auth?client_id=aem-bruker.com&redirect_uri=https%3A%2F%2Fwww.bruker.com%2Fen.login.html%3FtargetUrl%3Dhttps%3A%2F%2Fwww.bruker.com%2Fen%2Fservices%2Fsoftware-downloads%2Fmass-spectrometry.html&response_type=id_token%20token&scope=openid%20profile&state=4f9d225e92f341cca3b03a55533dbd65&nonce=f550633b1e984ecfb07979ae6d9277b4&ui_locales=en> (after registering), using the 'OpenTIMS' C++ reader and save all into 'data.tables'.
Author: Mateusz Krzysztof Łącki [aut, cre, cph] (<https://orcid.org/0000-0001-7415-4748>), Michał Piotr Startek [aut, cph] (<https://orcid.org/0000-0001-5227-3447>)
Maintainer: Mateusz Krzysztof Łącki <matteo.lacki@gmail.com>

Diff between timsr versions 0.0.2 dated 2021-05-04 and 0.0.3 dated 2021-05-11

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Package stocc updated to version 1.31 with previous version 1.30 dated 2015-08-23

Title: Fit a Spatial Occupancy Model via Gibbs Sampling
Description: Fit a spatial-temporal occupancy models using a probit formulation instead of a traditional logit model.
Author: Devin S. Johnson
Maintainer: Devin S. Johnson <devin.johnson@noaa.gov>

Diff between stocc versions 1.30 dated 2015-08-23 and 1.31 dated 2021-05-11

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Package netmeta updated to version 1.4-0 with previous version 1.3-0 dated 2021-01-18

Title: Network Meta-Analysis using Frequentist Methods
Description: A comprehensive set of functions providing frequentist methods for network meta-analysis and supporting Schwarzer et al. (2015) <DOI:10.1007/978-3-319-21416-0>, Chapter 8 "Network Meta-Analysis": - frequentist network meta-analysis following Rücker (2012) <DOI:10.1002/jrsm.1058>; - net heat plot and design-based decomposition of Cochran's Q according to Krahn et al. (2013) <DOI:10.1186/1471-2288-13-35>; - measures characterizing the flow of evidence between two treatments by König et al. (2013) <DOI:10.1002/sim.6001>; - ranking of treatments (frequentist analogue of SUCRA) according to Rücker & Schwarzer (2015) <DOI:10.1186/s12874-015-0060-8>; - partial order of treatment rankings ('poset') and Hasse diagram for 'poset' (Carlsen & Bruggemann, 2014) <DOI:10.1002/cem.2569>; (Rücker & Schwarzer, 2017) <DOI:10.1002/jrsm.1270>; - split direct and indirect evidence to check consistency (Dias et al., 2010) <DOI:10.1002/sim.3767>, (Efthimiou et al., 2019) <DOI:10.1002/sim.8158>; - league table with network meta-analysis results; - additive network meta-analysis for combinations of treatments (Rücker et al., 2019) <DOI:10.1002/bimj.201800167>; - network meta-analysis of binary data using the Mantel-Haenszel or non-central hypergeometric distribution method (Efthimiou et al., 2019) <DOI:10.1002/sim.8158>; - 'comparison-adjusted' funnel plot (Chaimani & Salanti, 2012) <DOI:10.1002/jrsm.57>; - automated drawing of network graphs described in Rücker & Schwarzer (2016) <DOI:10.1002/jrsm.1143>.
Author: Gerta Rücker [aut] (<https://orcid.org/0000-0002-2192-2560>), Ulrike Krahn [aut], Jochem König [aut] (<https://orcid.org/0000-0003-4683-0360>), Orestis Efthimiou [aut] (<https://orcid.org/0000-0002-0955-7572>), Guido Schwarzer [aut, cre] (<https://orcid.org/0000-0001-6214-9087>)
Maintainer: Guido Schwarzer <sc@imbi.uni-freiburg.de>

Diff between netmeta versions 1.3-0 dated 2021-01-18 and 1.4-0 dated 2021-05-11

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Package diagmeta updated to version 0.4-1 with previous version 0.4-0 dated 2020-04-02

Title: Meta-Analysis of Diagnostic Accuracy Studies with Several Cutpoints
Description: Provides methods by Steinhauser et al. (2016) <DOI:10.1186/s12874-016-0196-1> for meta-analysis of diagnostic accuracy studies with several cutpoints.
Author: Gerta Rücker [aut] (<https://orcid.org/0000-0002-2192-2560>), Susanne Steinhauser [aut], Srinath Kolampally [aut], Guido Schwarzer [aut, cre] (<https://orcid.org/0000-0001-6214-9087>)
Maintainer: Guido Schwarzer <sc@imbi.uni-freiburg.de>

Diff between diagmeta versions 0.4-0 dated 2020-04-02 and 0.4-1 dated 2021-05-11

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Package cleanr updated to version 1.3.2 with previous version 1.3.1 dated 2020-11-20

Title: Helps You to Code Cleaner
Description: Check your R code for some of the most common layout flaws. Many tried to teach us how to write code less dreadful, be it implicitly as B. W. Kernighan and D. M. Ritchie (1988) <ISBN:0-13-110362-8> in 'The C Programming Language' did, be it explicitly as R.C. Martin (2008) <ISBN:0-13-235088-2> in 'Clean Code: A Handbook of Agile Software Craftsmanship' did. So we should check our code for files too long or wide, functions with too many lines, too wide lines, too many arguments or too many levels of nesting. Note: This is not a static code analyzer like pylint or the like. Checkout <https://cran.r-project.org/package=lintr> instead.
Author: Andreas Dominik Cullmann [aut, cre]
Maintainer: Andreas Dominik Cullmann <fvafrcu@mailbox.org>

Diff between cleanr versions 1.3.1 dated 2020-11-20 and 1.3.2 dated 2021-05-11

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Package PASSED updated to version 1.1-0 with previous version 1.0-3 dated 2020-07-21

Title: Calculate Power and Sample Size for Two Sample Mean Tests
Description: Power calculations are a critical component of any research study to determine the minimum sample size necessary to detect differences between multiple groups. Here we present an 'R' package, 'PASSED', that performs power and sample size calculations for the test of two-sample means or ratios with data following beta, gamma (Chang et al. (2011), <doi:10.1007/s00180-010-0209-1>), normal, Poisson (Gu et al. (2008), <doi:10.1002/bimj.200710403>), binomial, geometric, and negative binomial (Zhu and Lakkis (2014), <doi:10.1002/sim.5947>) distributions.
Author: Jinpu Li [aut, cre], Ryan Knigge [aut], Kaiyi Chen [aut], Emily Leary [aut]
Maintainer: Jinpu Li <lijinp@health.missouri.edu>

Diff between PASSED versions 1.0-3 dated 2020-07-21 and 1.1-0 dated 2021-05-11

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New package TensorComplete with initial version 0.1.0
Package: TensorComplete
Title: Tensor Noise Reduction and Completion Methods
Version: 0.1.0
Author: Chanwoo Lee <chanwoo.lee@wisc.edu>, Miaoyan Wang <miaoyan.wang@wisc.edu>
Maintainer: Chanwoo Lee <chanwoo.lee@wisc.edu>
Imports: pracma, methods, utils, tensorregress, MASS
Description: Efficient algorithms for tensor noise reduction and completion. This package includes a suite of parametric and nonparametric tools for estimating tensor signals from noisy, possibly incomplete observations. The methods allow a broad range of data types, including continuous, binary, and ordinal-valued tensor entries. The algorithms employ the alternating optimization. The detailed algorithm description can be found in the following three references.
URL: Chanwoo Lee and Miaoyan Wang. Tensor denoising and completion based on ordinal observations. ICML, 2020. http://proceedings.mlr.press/v119/lee20i.html Chanwoo Lee and Miaoyan Wang. Beyond the Signs: Nonparametric tensor completion via sign series. 2021. https://arxiv.org/abs/2102.00384 Chanwoo Lee, Lexin Li, Hao Helen Zhang, and Miaoyan Wang. Nonparametric trace regression in high dimensions via sign series representation. 2021. https://arxiv.org/abs/2105.01783
License: GPL (>= 2)
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2021-05-10 19:16:04 UTC; chanwoolee
Repository: CRAN
Date/Publication: 2021-05-11 14:52:15 UTC

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New package SportsTour with initial version 0.1.0
Package: SportsTour
Title: Display Tournament Fixtures using Knock Out and Round Robin Techniques
Version: 0.1.0
Authors@R: c(person("Sunil","Kumar",role="aut"),person("Ankit","Tanwar",role="cre",email="ankit6.tanwar@gmail.com"))
Description: Use of Knock Out and Round Robin Techniques in preparing tournament fixtures as discussed in the Book Health and Physical Education by 'Dr. V K Sharma'(2018,ISBN:978-93-5272-134-4).
License: GPL
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2021-05-10 12:17:45 UTC; Ayushi Tanwar
Author: Sunil Kumar [aut], Ankit Tanwar [cre]
Maintainer: Ankit Tanwar <ankit6.tanwar@gmail.com>
Repository: CRAN
Date/Publication: 2021-05-11 14:12:11 UTC

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Package sjlabelled updated to version 1.1.8 with previous version 1.1.7 dated 2020-09-24

Title: Labelled Data Utility Functions
Description: Collection of functions dealing with labelled data, like reading and writing data between R and other statistical software packages like 'SPSS', 'SAS' or 'Stata', and working with labelled data. This includes easy ways to get, set or change value and variable label attributes, to convert labelled vectors into factors or numeric (and vice versa), or to deal with multiple declared missing values.
Author: Daniel Lüdecke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>), avid Ranzolin [ctb], Jonathan De Troye [ctb]
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

Diff between sjlabelled versions 1.1.7 dated 2020-09-24 and 1.1.8 dated 2021-05-11

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Package Signac updated to version 1.2.1 with previous version 1.2.0 dated 2021-04-28

Title: Analysis of Single-Cell Chromatin Data
Description: A framework for the analysis and exploration of single-cell chromatin data. The 'Signac' package contains functions for quantifying single-cell chromatin data, computing per-cell quality control metrics, dimension reduction and normalization, visualization, and DNA sequence motif analysis. Reference: Stuart et al. (2020) <doi:10.1101/2020.11.09.373613>.
Author: Tim Stuart [aut, cre] (<https://orcid.org/0000-0002-3044-0897>), Avi Srivastava [aut] (<https://orcid.org/0000-0001-9798-2079>), Paul Hoffman [ctb] (<https://orcid.org/0000-0002-7693-8957>), Rahul Satija [ctb] (<https://orcid.org/0000-0001-9448-8833>)
Maintainer: Tim Stuart <tstuart@nygenome.org>

Diff between Signac versions 1.2.0 dated 2021-04-28 and 1.2.1 dated 2021-05-11

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New package rainette with initial version 0.1.3
Package: rainette
Title: The Reinert Method for Textual Data Clustering
Version: 0.1.3
Date: 2021-05-10
Authors@R: c(person("Julien", "Barnier", email="julien.barnier@cnrs.fr", role=c("aut","cre")), person("Florian", "Privé", email="florian.prive.21@gmail.com", role="ctb"))
Maintainer: Julien Barnier <julien.barnier@cnrs.fr>
Description: An R implementation of the Reinert text clustering method. For more details about the algorithm see the included vignettes or Reinert (1990) <doi:10.1177/075910639002600103>.
License: GPL (>= 3)
VignetteBuilder: knitr
URL: https://juba.github.io/rainette/
BugReports: https://github.com/juba/rainette/issues
Encoding: UTF-8
Imports: dplyr (>= 0.8.3), tidyr, purrr, ggplot2, stringr, quanteda (>= 2.1), quanteda.textstats, RSpectra, dendextend, ggwordcloud, gridExtra, rlang, RColorBrewer, shiny, miniUI, formatR, highr, progressr, Rcpp (>= 1.0.3)
Suggests: testthat, knitr, rmarkdown, covr, tm, FNN, quanteda.textmodels
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2021-05-10 12:32:16 UTC; julien
Author: Julien Barnier [aut, cre], Florian Privé [ctb]
Repository: CRAN
Date/Publication: 2021-05-11 14:30:02 UTC

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New package memoiR with initial version 0.5-0
Package: memoiR
Title: R Markdown and Bookdown Templates to Publish Documents
Version: 0.5-0
URL: https://github.com/EricMarcon/memoiR
BugReports: https://github.com/EricMarcon/memoiR/issues
Authors@R: person(given = "Eric", family = "Marcon", role = c("aut", "cre"), email = "eric.marcon@agroparistech.fr", comment = c(ORCID = "0000-0002-5249-321X"))
Description: Producing high-quality documents suitable for publication directly from R is made possible by the R Markdown ecosystem. 'memoiR' makes it easy. It provides templates to knit memoirs, articles and slideshows with helpers to publish the documents on GitHub Pages and activate continuous integration.
License: GPL (>= 3)
Encoding: UTF-8
SystemRequirements: pandoc
VignetteBuilder: knitr
Imports: bookdown, rmarkdown, usethis
Suggests: knitr, pkgdown, rmdformats, testthat
NeedsCompilation: no
Packaged: 2021-05-10 14:09:21 UTC; emarc
Author: Eric Marcon [aut, cre] (<https://orcid.org/0000-0002-5249-321X>)
Maintainer: Eric Marcon <eric.marcon@agroparistech.fr>
Repository: CRAN
Date/Publication: 2021-05-11 14:20:03 UTC

More information about memoiR at CRAN
Permanent link

New package academictwitteR with initial version 0.1.0
Package: academictwitteR
Title: Access the Twitter Academic Research Product Track V2 API Endpoint
Version: 0.1.0
Authors@R: c(person(given = "Christopher", family = "Barrie", role = c("aut", "cre"), email = "christopher.barrie@ed.ac.uk", comment = c(ORCID = "0000-0002-9156-990X")), person(given = "Justin Chun-ting", family = "Ho", role = c("aut"), email = "justin.chunting.ho@sciencespo.fr", comment = c(ORCID = "0000-0002-7884-1059")))
Description: Package to query the Twitter Academic Research Product Track (<https://developer.twitter.com/en/solutions/academic-research>), providing access to full-archive search and other v2 API endpoints. Functions are written with academic research in mind. They provide flexibility in how the user wishes to store collected data, and encourage regular storage of data to mitigate loss when collecting large volumes of tweets. They also provide workarounds to manage and reshape the format in which data is provided on the client side.
License: MIT + file LICENSE
URL: https://github.com/cjbarrie/academictwitteR
BugReports: https://github.com/cjbarrie/academictwitteR/issues
Encoding: UTF-8
Imports: dplyr, httr, jsonlite
Suggests: knitr, rmarkdown, devtools
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-05-10 15:59:00 UTC; cbarrie6
Author: Christopher Barrie [aut, cre] (<https://orcid.org/0000-0002-9156-990X>), Justin Chun-ting Ho [aut] (<https://orcid.org/0000-0002-7884-1059>)
Maintainer: Christopher Barrie <christopher.barrie@ed.ac.uk>
Repository: CRAN
Date/Publication: 2021-05-11 14:52:12 UTC

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Permanent link

Package survivoR updated to version 0.9.3 with previous version 0.9.2 dated 2021-04-06

Title: Data from all Seasons of Survivor (US) TV Series in Tidy Format
Description: Several datasets which detail the results and events of each season of Survivor. This includes details on the cast, voting history, immunity and reward challenges, jury votes and viewers. This data is useful for practicing data wrangling, graph analytics and analysing how each season of Survivor played out. Includes 'ggplot2' scales and colour palettes for visualisation.
Author: Daniel Oehm [aut, cre]
Maintainer: Daniel Oehm <danieloehm@gmail.com>

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Package Kernelheaping updated to version 2.2.8 with previous version 2.2.2 dated 2020-02-21

Title: Kernel Density Estimation for Heaped and Rounded Data
Description: In self-reported or anonymised data the user often encounters heaped data, i.e. data which are rounded (to a possibly different degree of coarseness). While this is mostly a minor problem in parametric density estimation the bias can be very large for non-parametric methods such as kernel density estimation. This package implements a partly Bayesian algorithm treating the true unknown values as additional parameters and estimates the rounding parameters to give a corrected kernel density estimate. It supports various standard bandwidth selection methods. Varying rounding probabilities (depending on the true value) and asymmetric rounding is estimable as well: Gross, M. and Rendtel, U. (2016) (<doi:10.1093/jssam/smw011>). Additionally, bivariate non-parametric density estimation for rounded data, Gross, M. et al. (2016) (<doi:10.1111/rssa.12179>), as well as data aggregated on areas is supported.
Author: Marcus Gross [aut, cre], Kerstin Erfurth [ctb]
Maintainer: Marcus Gross <marcus.gross@inwt-statistics.de>

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Package apexcharter updated to version 0.2.0 with previous version 0.1.8 dated 2020-11-18

Title: Create Interactive Chart with the JavaScript 'ApexCharts' Library
Description: Provides an 'htmlwidgets' interface to 'apexcharts.js'. 'Apexcharts' is a modern JavaScript charting library to build interactive charts and visualizations with simple API. 'Apexcharts' examples and documentation are available here: <https://apexcharts.com/>.
Author: Victor Perrier [aut, cre], Fanny Meyer [aut], Juned Chhipa [cph] (apexcharts.js library), Mike Bostock [cph] (d3.format library)
Maintainer: Victor Perrier <victor.perrier@dreamrs.fr>

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Package textshaping updated to version 0.3.4 with previous version 0.3.3 dated 2021-03-16

Title: Bindings to the 'HarfBuzz' and 'Fribidi' Libraries for Text Shaping
Description: Provides access to the text shaping functionality in the 'HarfBuzz' library and the bidirectional algorithm in the 'Fribidi' library. 'textshaping' is a low-level utility package mainly for graphic devices that expands upon the font tool-set provided by the 'systemfonts' package.
Author: Thomas Lin Pedersen [cre, aut] (<https://orcid.org/0000-0002-5147-4711>), RStudio [cph]
Maintainer: Thomas Lin Pedersen <thomas.pedersen@rstudio.com>

Diff between textshaping versions 0.3.3 dated 2021-03-16 and 0.3.4 dated 2021-05-11

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Package systemfonts updated to version 1.0.2 with previous version 1.0.1 dated 2021-02-09

Title: System Native Font Finding
Description: Provides system native access to the font catalogue. As font handling varies between systems it is difficult to correctly locate installed fonts across different operating systems. The 'systemfonts' package provides bindings to the native libraries on Windows, macOS and Linux for finding font files that can then be used further by e.g. graphic devices. The main use is intended to be from compiled code but 'systemfonts' also provides access from R.
Author: Thomas Lin Pedersen [aut, cre] (<https://orcid.org/0000-0002-5147-4711>), Jeroen Ooms [aut] (<https://orcid.org/0000-0002-4035-0289>), Devon Govett [aut] (Author of font-manager), RStudio [cph]
Maintainer: Thomas Lin Pedersen <thomas.pedersen@rstudio.com>

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Package proceduralnames updated to version 0.1.2 with previous version 0.1.1 dated 2021-01-07

Title: Several Methods for Procedural Name Generation
Description: A small, dependency-free way to generate random names. Methods provided include the adjective-surname approach of Docker containers ('<https://github.com/moby/moby/blob/master/pkg/namesgenerator/names-generator.go'), and combinations of common English or Spanish words.
Author: Michael Mahoney [aut, cre] (<https://orcid.org/0000-0003-2402-304X>)
Maintainer: Michael Mahoney <mike.mahoney.218@gmail.com>

Diff between proceduralnames versions 0.1.1 dated 2021-01-07 and 0.1.2 dated 2021-05-11

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Package BiocManager updated to version 1.30.15 with previous version 1.30.14 dated 2021-05-10

Title: Access the Bioconductor Project Package Repository
Description: A convenient tool to install and update Bioconductor packages.
Author: Martin Morgan [aut] (<https://orcid.org/0000-0002-5874-8148>), Marcel Ramos [ctb, cre] (<https://orcid.org/0000-0002-3242-0582>)
Maintainer: Marcel Ramos <marcel.ramos@roswellpark.org>

Diff between BiocManager versions 1.30.14 dated 2021-05-10 and 1.30.15 dated 2021-05-11

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Package SpATS updated to version 1.0-13 with previous version 1.0-12 dated 2021-02-26

Title: Spatial Analysis of Field Trials with Splines
Description: Analysis of field trial experiments by modelling spatial trends using two-dimensional Penalised spline (P-spline) models.
Author: Maria Xose Rodriguez-Alvarez [aut, cre], Martin Boer [aut], Paul Eilers [aut], Fred van Eeuwijk [ctb]
Maintainer: Maria Xose Rodriguez-Alvarez <mxrodriguez@bcamath.org>

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New package tabula with initial version 1.6.0
Package: tabula
Title: Analysis, Seriation and Visualization of Archaeological Count Data
Version: 1.6.0
Authors@R: c(person(given = "Nicolas", family = "Frerebeau", role = c("aut", "cre"), email = "nicolas.frerebeau@u-bordeaux-montaigne.fr", comment = c(ORCID = "0000-0001-5759-4944")), person(given = "Brice", family = "Lebrun", role = "ctb", email = "brice.lebrun@u-bordeaux-montaigne.fr", comment = c(ORCID = "0000-0001-7503-8685")), person(given = "Matthew", family = "Peeples", role = "ctb", email = "matthew.peeples@asu.edu", comment = c(ORCID = "0000-0003-4496-623X")), person(given = "Ben", family = "Marwick", role = "ctb", email = "bmarwick@uw.edu", comment = c(ORCID = "0000-0001-7879-4531")), person(given = "Anne", family = "Philippe", role = "ctb", email = "anne.philippe@univ-nantes.fr", comment = c(ORCID = "0000-0002-5331-5087")), person(given = "Jean-Baptiste", family = "Fourvel", role = "ctb", email = "fourvel@mmsh.univ-aix.fr", comment = c(ORCID = "0000-0002-1061-4642")))
Maintainer: Nicolas Frerebeau <nicolas.frerebeau@u-bordeaux-montaigne.fr>
Description: An easy way to examine archaeological count data. This package provides a convenient and reproducible toolkit for relative and absolute dating and analysis of (chronological) patterns. It includes functions for matrix seriation (reciprocal ranking, CA-based seriation), chronological modeling and dating of archaeological assemblages and/or objects. Beyond these, the package provides several tests and measures of diversity: heterogeneity and evenness (Brillouin, Shannon, Simpson, etc.), richness and rarefaction (Chao1, Chao2, ACE, ICE, etc.), turnover and similarity (Brainerd-Robinson, etc.). The package make it easy to visualize count data and statistical thresholds: rank vs abundance plots, heatmaps, Ford (1962) and Bertin (1977) diagrams.
License: GPL-3
URL: https://tabula.tesselle.org, https://github.com/tesselle/tabula
BugReports: https://github.com/tesselle/tabula/issues
Depends: R (>= 3.3)
Imports: arkhe (>= 0.3.0), dimensio, ggplot2, grDevices, methods, rlang, stats, utils
Suggests: covr, folio, khroma, knitr, magrittr, rmarkdown, testthat (>= 3.0.0), vdiffr
VignetteBuilder: knitr
Encoding: UTF-8
Collate: 'AllClasses.R' 'AllGenerics.R' 'coerce.R' 'date_event.R' 'date_mcd.R' 'deprecate.R' 'ggplot2.R' 'index_diversity.R' 'index_heterogeneity.R' 'index_rarefaction.R' 'index_richness.R' 'index_similarity.R' 'index_turnover.R' 'initialize.R' 'mutators.R' 'permute.R' 'plot_bertin.R' 'plot_date.R' 'plot_diversity.R' 'plot_ford.R' 'plot_heatmap.R' 'plot_rank.R' 'plot_spot.R' 'plot_time.R' 'reexport.R' 'refine_ca.R' 'refine_event.R' 'seriate_average.R' 'seriate_rank.R' 'show.R' 'statistics.R' 'subset.R' 'tabula-package.R' 'test_diversity.R' 'test_fit.R' 'utilities.R' 'validate.R' 'zzz.R'
NeedsCompilation: no
Packaged: 2021-05-04 14:03:39 UTC; nicolas
Author: Nicolas Frerebeau [aut, cre] (<https://orcid.org/0000-0001-5759-4944>), Brice Lebrun [ctb] (<https://orcid.org/0000-0001-7503-8685>), Matthew Peeples [ctb] (<https://orcid.org/0000-0003-4496-623X>), Ben Marwick [ctb] (<https://orcid.org/0000-0001-7879-4531>), Anne Philippe [ctb] (<https://orcid.org/0000-0002-5331-5087>), Jean-Baptiste Fourvel [ctb] (<https://orcid.org/0000-0002-1061-4642>)
Repository: CRAN
Date/Publication: 2021-05-11 11:40:02 UTC

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Package shinyMatrix updated to version 0.5.0 with previous version 0.4.0 dated 2020-10-05

Title: Shiny Matrix Input Field
Description: Implements a custom matrix input field.
Author: Andreas Neudecker
Maintainer: Andreas Neudecker <andreas.neudecker@inwt-statistics.de>

Diff between shinyMatrix versions 0.4.0 dated 2020-10-05 and 0.5.0 dated 2021-05-11

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Package pensim updated to version 1.3.3 with previous version 1.3.2 dated 2020-04-20

Title: Simulation of High-Dimensional Data and Parallelized Repeated Penalized Regression
Description: Simulation of continuous, correlated high-dimensional data with time to event or binary response, and parallelized functions for Lasso, Ridge, and Elastic Net penalized regression with repeated starts and two-dimensional tuning of the Elastic Net.
Author: Levi Waldron <lwaldron.research@gmail.com>
Maintainer: Levi Waldron <lwaldron.research@gmail.com>

Diff between pensim versions 1.3.2 dated 2020-04-20 and 1.3.3 dated 2021-05-11

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Package corrplot updated to version 0.88 with previous version 0.87 dated 2021-05-08

Title: Visualization of a Correlation Matrix
Description: A graphical display of a correlation matrix or general matrix. It also contains some algorithms to do matrix reordering. In addition, corrplot is good at details, including choosing color, text labels, color labels, layout, etc.
Author: Taiyun Wei [cre, aut], Viliam Simko [aut], Michael Levy [ctb], Yihui Xie [ctb], Yan Jin [ctb], Jeff Zemla [ctb], Moritz Freidank [ctb], Jun Cai [ctb], Tomas Protivinsky [ctb]
Maintainer: Taiyun Wei <weitaiyun@gmail.com>

Diff between corrplot versions 0.87 dated 2021-05-08 and 0.88 dated 2021-05-11

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Package clam updated to version 2.3.9 with previous version 2.3.8 dated 2021-01-23

Title: Classical Age-Depth Modelling of Cores from Deposits
Description: Performs 'classical' age-depth modelling of dated sediment deposits - prior to applying more sophisticated techniques such as Bayesian age-depth modelling. Any radiocarbon dated depths are calibrated. Age-depth models are constructed by sampling repeatedly from the dated levels, each time drawing age-depth curves. Model types include linear interpolation, linear or polynomial regression, and a range of splines. See Blaauw (2010). <doi:10.1016/j.quageo.2010.01.002>.
Author: Maarten Blaauw [aut, cre], J. Andres Christen [ctb], Judith Esquivel Vazquez [ctb], Simon Goring [ctb]
Maintainer: Maarten Blaauw <maarten.blaauw@qub.ac.uk>

Diff between clam versions 2.3.8 dated 2021-01-23 and 2.3.9 dated 2021-05-11

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Package bmixture updated to version 1.7 with previous version 1.6 dated 2020-05-26

Title: Bayesian Estimation for Finite Mixture of Distributions
Description: Provides statistical tools for Bayesian estimation of mixture distributions, mainly a mixture of Gamma, Normal, and t-distributions. The package is implemented based on the Bayesian literature for the finite mixture of distributions, including Mohammadi and et al. (2013) <doi:10.1007/s00180-012-0323-3> and Mohammadi and Salehi-Rad (2012) <doi:10.1080/03610918.2011.588358>.
Author: Reza Mohammadi [aut, cre] (<https://orcid.org/0000-0001-9538-0648>)
Maintainer: Reza Mohammadi <a.mohammadi@uva.nl>

Diff between bmixture versions 1.6 dated 2020-05-26 and 1.7 dated 2021-05-11

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Package IRkernel updated to version 1.2 with previous version 1.1.1 dated 2020-07-20

Title: Native R Kernel for the 'Jupyter Notebook'
Description: The R kernel for the 'Jupyter' environment executes R code which the front-end ('Jupyter Notebook' or other front-ends) submits to the kernel via the network.
Author: Thomas Kluyver [aut, cph], Philipp Angerer [aut, cph, cre] (<https://orcid.org/0000-0002-0369-2888>), Jan Schulz [aut, cph], Karthik Ram [aut, cph]
Maintainer: Philipp Angerer <phil.angerer@gmail.com>

Diff between IRkernel versions 1.1.1 dated 2020-07-20 and 1.2 dated 2021-05-11

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New package vsd with initial version 0.1.0
Package: vsd
Title: Graphical Shim for Visual Survival Data Analysis
Version: 0.1.0
Authors@R: c(person(given = "Daniel", family = "Camacho", role = c("aut", "cre"), email = "2016711@student.uma.pt", comment = c(ORCID = "0000-0002-4980-9391")), person(given = "Ana", family = "Abreu", role = c("aut", "ths"), email = "abreu@staff.uma.pt", comment = c(ORCID = "0000-0002-6155-8492")))
Description: Provides a shim command for survival analysis graphic generation.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: survival, ggplot2
Imports: dplyr, survminer, flexsurv, magrittr, ggpubr, muhaz
Suggests: plotly
Language: en-US
Collate: 'options.R' 'plot_forest.R' 'plot_hazard.R' 'plot_parametric.R' 'util.R' 'vsd-package.R' 'vsd.R'
NeedsCompilation: no
Packaged: 2021-05-10 11:15:14 UTC; dusty
Author: Daniel Camacho [aut, cre] (<https://orcid.org/0000-0002-4980-9391>), Ana Abreu [aut, ths] (<https://orcid.org/0000-0002-6155-8492>)
Maintainer: Daniel Camacho <2016711@student.uma.pt>
Repository: CRAN
Date/Publication: 2021-05-11 09:40:02 UTC

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New package ssimparser with initial version 0.1.0
Package: ssimparser
Title: Standard Schedules Information Parser
Version: 0.1.0
Author: Sebastien Thonnard
Maintainer: Sebastien Thonnard <sebastien.thonnard@icloud.com>
Description: Parse Standard Schedules Information file (types 2 and 3) into a Data Frame. Can also expand schedules into flights.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: false
Imports: tidyr, dplyr, stringr, airportr, magrittr
NeedsCompilation: no
Packaged: 2021-05-02 16:58:55 UTC; sebastienthonnard
Repository: CRAN
Date/Publication: 2021-05-11 09:10:02 UTC

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New package snap with initial version 1.0.0
Package: snap
Title: Simple Neural Application
Version: 1.0.0
Author: Giancarlo Vercellino
Maintainer: Giancarlo Vercellino <giancarlo.vercellino@gmail.com>
Description: A simple wrapper to easily design vanilla deep neural networks using 'Tensorflow'/'Keras' backend for regression, classification and multi-label tasks, with some tweaks and tricks (skip shortcuts, embedding, feature selection and anomaly detection).
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.6)
Imports: keras, tensorflow, dplyr, purrr, forcats, tictoc, readr, ggplot2, CORElearn, dbscan, stringr, reticulate
URL: https://keras.rstudio.com, https://rdrr.io/cran/dbscan/man/lof.html, https://www.rdocumentation.org/packages/CORElearn/versions/1.56.0/topics/attrEval
NeedsCompilation: no
Packaged: 2021-05-10 06:18:55 UTC; gvercellino
Repository: CRAN
Date/Publication: 2021-05-11 09:40:05 UTC

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New package rtrend with initial version 0.1.0
Package: rtrend
Title: Trend Estimating Tools
Description: The traditional linear regression trend, Modified Mann-Kendall (MK) non-parameter trend and bootstrap trend are included in this package. Linear regression trend is rewritten by '.lm.fit'. MK trend is rewritten by 'Rcpp'. Finally, those functions are about 10 times faster than previous version in R. Reference: Hamed, K. H., & Rao, A. R. (1998). A modified Mann-Kendall trend test for autocorrelated data. Journal of hydrology, 204(1-4), 182-196. <doi:10.1016/S0022-1694(97)00125-X>.
Version: 0.1.0
Authors@R: c( person("Dongdong", "Kong", role = c("aut", "cre"), email = "kongdd.sysu@gmail.com", comment = c(ORCID = "0000-0003-1836-8172")))
License: MIT + file LICENSE
Encoding: UTF-8
LinkingTo: Rcpp
Imports: Rcpp, fftwtools, boot, magrittr, matrixStats, ggplot2
Suggests: covr, testthat (>= 3.0.0)
URL: https://github.com/rpkgs/rtrend
BugReports: https://github.com/rpkgs/rtrend/issues
NeedsCompilation: yes
Packaged: 2021-05-09 13:28:50 UTC; kongdd
Author: Dongdong Kong [aut, cre] (<https://orcid.org/0000-0003-1836-8172>)
Maintainer: Dongdong Kong <kongdd.sysu@gmail.com>
Repository: CRAN
Date/Publication: 2021-05-11 09:00:02 UTC

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Package quanteda.textstats updated to version 0.94.1 with previous version 0.94 dated 2021-04-06

Title: Textual Statistics for the Quantitative Analysis of Textual Data
Description: Textual statistics functions formerly in the 'quanteda' package. Textual statistics for characterizing and comparing textual data. Includes functions for measuring term and document frequency, the co-occurrence of words, similarity and distance between features and documents, feature entropy, keyword occurrence, readability, and lexical diversity. These functions extend the 'quanteda' package and are specially designed for sparse textual data.
Author: Kenneth Benoit [cre, aut, cph] (<https://orcid.org/0000-0002-0797-564X>), Kohei Watanabe [aut] (<https://orcid.org/0000-0001-6519-5265>), Haiyan Wang [aut] (<https://orcid.org/0000-0003-4992-4311>), Jiong Wei Lua [aut], Jouni Kuha [aut] (<https://orcid.org/0000-0002-1156-8465>), European Research Council [fnd] (ERC-2011-StG 283794-QUANTESS)
Maintainer: Kenneth Benoit <kbenoit@lse.ac.uk>

Diff between quanteda.textstats versions 0.94 dated 2021-04-06 and 0.94.1 dated 2021-05-11

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New package nsdr with initial version 0.1.0
Package: nsdr
Title: Nonlinear Sufficient Dimension Reduction
Version: 0.1.0
Authors@R: c(person(given = "Bing", family = "Li", role = "aut"), person(given = "Kyongwon", family = "Kim", role = c("aut", "cre"), email = "kimk@ewha.ac.kr"))
Description: Provides tools to implement both unsupervised and supervised nonlinear dimension reduction methods. Principal Component Analysis (PCA), Sliced Inverse Regression (SIR), and Sliced Average Variance Estimation (SAVE) are useful methods to reduce the dimensionality of covariates. However, they produce linear combinations of covariates. Kernel PCA, generalized SIR, and generalized SAVE address this problem by extending the applicability of the dimension reduction problem to nonlinear settings. This package includes a comprehensive algorithm for kernel PCA, generalized SIR, and generalized SAVE, including methods for choosing tuning parameters and some essential functions. The algorithms for this package is from Li (2018, ISBN:9780367734725).
Depends: R (>= 3.5.0)
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2021-05-09 22:10:57 UTC; kyongwon
Author: Bing Li [aut], Kyongwon Kim [aut, cre]
Maintainer: Kyongwon Kim <kimk@ewha.ac.kr>
Repository: CRAN
Date/Publication: 2021-05-11 09:30:02 UTC

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Package mailmerge updated to version 0.2.1 with previous version 0.2.0 dated 2021-04-12

Title: Mail Merge Using R Markdown Documents and 'gmailr'
Description: Mail merge using markdown documents and gmail. With this package you can parse markdown documents as the body of email, and the 'yaml' header to specify the subject line of the email. Any '{}' braces in the email will be encoded with 'glue::glue()'. You can preview the email in the RStudio viewer pane, and send (draft) email using 'gmailr'.
Author: Andrie de Vries [aut, cre]
Maintainer: Andrie de Vries <apdevries@gmail.com>

Diff between mailmerge versions 0.2.0 dated 2021-04-12 and 0.2.1 dated 2021-05-11

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New package MTE with initial version 1.0.1
Package: MTE
Title: Maximum Tangent Likelihood Estimation for Linear Regression
Version: 1.0.1
Authors@R: c(person("Shaobo", "Li", email="shaobo.li@ku.edu", role=c("aut", "cre")), person("Yichen", "Qin", email="qinyn@ucmail.uc.edu", role=c("aut")))
Maintainer: Shaobo Li <shaobo.li@ku.edu>
Description: Several robust estimators for linear regression and variable selection are provided. Included are Maximum tangent likelihood estimator (Qin, et al., 2017), least absolute deviance estimator and Huber regression. The penalized version of each of these estimator incorporates L1 penalty function, i.e., LASSO and Adaptive Lasso. They are able to produce consistent estimates for both fixed and high-dimensional settings.
URL: GitHub: https://github.com/shaobo-li/MTE
Depends: R (>= 3.1.0)
License: GPL-3
Imports: stats, quantreg, glmnet
NeedsCompilation: no
Packaged: 2021-05-09 17:29:49 UTC; lisha
Author: Shaobo Li [aut, cre], Yichen Qin [aut]
Repository: CRAN
Date/Publication: 2021-05-11 09:12:14 UTC

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Package leaflet.minicharts updated to version 0.6.2 with previous version 0.6.0 dated 2019-11-27

Title: Mini Charts for Interactive Maps
Description: Add and modify small charts on an interactive map created with package 'leaflet'. These charts can be used to represent at same time multiple variables on a single map.
Author: Veronique Bachelier [aut, cre], Jalal-Edine ZAWAM [aut], Benoit Thieurmel [aut], Francois Guillem [aut], RTE [cph]
Maintainer: Veronique Bachelier <veronique.bachelier@rte-france.com>

Diff between leaflet.minicharts versions 0.6.0 dated 2019-11-27 and 0.6.2 dated 2021-05-11

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New package highMLR with initial version 0.1.0
Title: Feature Selection for High Dimensional Survival Data
Package: highMLR
Version: 0.1.0
Date: 2021-05-08
Depends: R (>= 3.5.0)
Imports: mlr3, mlr3proba, mlr3learners, survival, gtools, tibble, dplyr, utils, coxme, missForest
LazyData: Yes
LazyDataCompression: xz
ByteCompile: Yes
Authors@R: c(person(("Atanu"), "Bhattacharjee", email="atanustat@gmail.com", role=c("aut", "cre","ctb")), person(("Gajendra"), "K. Vishwakarma", role=c("aut","ctb")), person(("Souvik"),"Banerjee", role=c("aut","ctb")))
Description: Perform high dimensional Feature Selection in the presence of survival outcome. Based on Feature Selection method and different survival analysis, it will obtain the best markers with optimal threshold levels according to their effect on disease progression and produce the most consistent level according to those threshold values. The functions' methodology is based on by Sonabend et al (2021) <doi:10.1093/bioinformatics/btab039> and Bhattacharjee et al (2021) <arXiv:2012.02102>.
License: GPL-3
Encoding: UTF-8
NeedsCompilation: no
Maintainer: Atanu Bhattacharjee <atanustat@gmail.com>
Packaged: 2021-05-10 10:45:29 UTC; Atanu
Author: Atanu Bhattacharjee [aut, cre, ctb], Gajendra K. Vishwakarma [aut, ctb], Souvik Banerjee [aut, ctb]
Repository: CRAN
Date/Publication: 2021-05-11 09:40:08 UTC

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Package dynRB updated to version 0.16 with previous version 0.15 dated 2018-12-18

Title: Dynamic Range Boxes
Description: Improves the concept of multivariate range boxes, which is highly susceptible for outliers and does not consider the distribution of the data. The package uses dynamic range boxes to overcome these problems.
Author: Manuela Schreyer <manuelalarissa.schreyer@sbg.ac.at>, Wolfgang Trutschnig <Wolfgang.Trutschnig@sbg.ac.at>, Robert R. Junker <Robert.Junker@sbg.ac.at>, Jonas Kuppler <Jonas.Kuppler@uni-duesseldorf.de>, Arne Bathke <Arne.Bathke@sbg.ac.at>, Judith H. Parkinson <judith.parkinson@sbg.ac.at>, Raoul Kutil <Raoul_Hugo.Kutil@stud.sbg.ac.at>
Maintainer: Florian Griessenberger <florian.griessenberger@sbg.ac.at>

Diff between dynRB versions 0.15 dated 2018-12-18 and 0.16 dated 2021-05-11

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Package ChaosGame updated to version 1.1 with previous version 1.0 dated 2021-03-01

Title: Chaos Game
Description: The main objective of the package is to enter a word of at least two letters based on which an Iterated Function System with Probabilities is constructed, and a two-dimensional fractal containing the chosen word infinitely often is generated via the Chaos Game. Additionally, the package allows to project the two-dimensional fractal on several three-dimensional surfaces and to transform the fractal into another fractal with uniform marginals.
Author: Florian Griessenberger [aut, cre], Manuela Schreyer [aut], Johannes Bartel [aut], Wolfgang Trutschnig [aut]
Maintainer: Florian Griessenberger <florian.griessenberger@sbg.ac.at>

Diff between ChaosGame versions 1.0 dated 2021-03-01 and 1.1 dated 2021-05-11

 DESCRIPTION |   11 +++++------
 MD5         |    4 ++--
 NAMESPACE   |    8 +++++++-
 3 files changed, 14 insertions(+), 9 deletions(-)

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Permanent link

New package bumblebee with initial version 0.1.0
Package: bumblebee
Title: Quantify Disease Transmission Within and Between Population Groups
Version: 0.1.0
Authors@R: c( person("Lerato E", "Magosi", email = "lmagosi@hsph.harvard.edu", role = "aut", comment = c(ORCID = "0000-0002-3388-9892")), person("Marc", "Lipsitch", email = "mlipsitc@hsph.harvard.edu", role = "aut"), person("Lerato E", "Magosi", email = "magosil86@gmail.com", role = "cre"))
Description: A simple tool to quantify the amount of transmission of an infectious disease of interest occurring within and between population groups. 'bumblebee' uses counts of observed directed transmission pairs, identified phylogenetically from deep-sequence data or from epidemiological contacts, to quantify transmission flows within and between population groups accounting for sampling heterogeneity. Population groups might include: geographical areas (e.g. communities, regions), demographic groups (e.g. age, gender) or arms of a randomized clinical trial. See the 'bumblebee' website for statistical theory, documentation and examples <https://magosil86.github.io/bumblebee/>.
License: MIT + file LICENSE
URL: https://magosil86.github.io/bumblebee/
BugReports: https://github.com/magosil86/bumblebee/issues
LazyData: true
Depends: R (>= 2.10)
Imports: dplyr (>= 1.0.2), gtools (>= 3.8.2), Hmisc (>= 4.4-2), magrittr (>= 2.0.1), rmarkdown (>= 2.6)
Suggests: covr (>= 3.5.1), knitr (>= 1.30), markdown (>= 1.1), testthat (>= 3.0.1)
Encoding: UTF-8
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-05-10 11:16:58 UTC; lmagosi
Author: Lerato E Magosi [aut] (<https://orcid.org/0000-0002-3388-9892>), Marc Lipsitch [aut], Lerato E Magosi [cre]
Maintainer: Lerato E Magosi <magosil86@gmail.com>
Repository: CRAN
Date/Publication: 2021-05-11 09:42:19 UTC

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Package proxyC updated to version 0.2.0 with previous version 0.1.5 dated 2019-07-21

Title: Computes Proximity in Large Sparse Matrices
Description: Computes proximity between rows or columns of large matrices efficiently in C++. Functions are optimised for large sparse matrices using the Armadillo and Intel TBB libraries. Among several built-in similarity/distance measures, computation of correlation, cosine similarity and Euclidean distance is particularly fast.
Author: Kohei Watanabe [cre, aut, cph] (<https://orcid.org/0000-0001-6519-5265>), Robrecht Cannoodt [aut] (<https://orcid.org/0000-0003-3641-729X>)
Maintainer: Kohei Watanabe <watanabe.kohei@gmail.com>

Diff between proxyC versions 0.1.5 dated 2019-07-21 and 0.2.0 dated 2021-05-11

 DESCRIPTION                 |   20 +++---
 MD5                         |   24 +++----
 NEWS.md                     |   40 ++++++++----
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 src/linear.cpp              |    7 +-
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 tests/testthat/test-dist.R  |   88 ++++++++++++++++++++-------
 tests/testthat/test-proxy.R |   95 +++++++++++++++++++----------
 tests/testthat/test-simil.R |   23 +++----
 13 files changed, 357 insertions(+), 198 deletions(-)

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Package dm updated to version 0.2.1 with previous version 0.2.0 dated 2021-05-03

Title: Relational Data Models
Description: Provides tools for working with multiple related tables, stored as data frames or in a relational database. Multiple tables (data and metadata) are stored in a compound object, which can then be manipulated with a pipe-friendly syntax.
Author: Tobias Schieferdecker [aut], Kirill Müller [aut, cre] (<https://orcid.org/0000-0002-1416-3412>), Darko Bergant [aut], Katharina Brunner [ctb], James Wondrasek [ctb], energie360° AG [fnd], cynkra GmbH [fnd, cph]
Maintainer: Kirill Müller <krlmlr+r@mailbox.org>

Diff between dm versions 0.2.0 dated 2021-05-03 and 0.2.1 dated 2021-05-11

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 dm-0.2.1/dm/tests/testthat/test-schema.R                        |    3 
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New package tarchetypes with initial version 0.2.0
Package: tarchetypes
Title: Archetypes for Targets
Description: Function-oriented Make-like declarative workflows for Statistics and data science are supported in the 'targets' R package. As an extension to 'targets', the 'tarchetypes' package provides convenient user-side functions to make 'targets' easier to use. By establishing reusable archetypes for common kinds of targets and pipelines, these functions help express complicated reproducible workflows concisely and compactly. The methods in this package were influenced by the 'drake' R package by Will Landau (2018) <doi:10.21105/joss.00550>.
Version: 0.2.0
License: MIT + file LICENSE
URL: https://docs.ropensci.org/tarchetypes/, https://github.com/ropensci/tarchetypes
BugReports: https://github.com/ropensci/tarchetypes/issues
Authors@R: c( person( given = c("William", "Michael"), family = "Landau", role = c("aut", "cre"), email = "will.landau@gmail.com", comment = c(ORCID = "0000-0003-1878-3253") ), person( given = "Samantha", family = "Oliver", role = "rev", comment = c(ORCID = "0000-0001-5668-1165") ), person( given = "Tristan", family = "Mahr", role = "rev", comment = c(ORCID = "0000-0002-8890-5116") ), person( family = "Eli Lilly and Company", role = "cph" ))
Depends: R (>= 3.5.0)
Imports: digest (>= 0.6.25), fs (>= 1.4.2), rlang (>= 0.4.7), targets (>= 0.4.1), tidyselect (>= 1.1.0), utils, vctrs (>= 0.3.4), withr (>= 2.1.2)
Suggests: curl (>= 4.3), dplyr (>= 1.0.0), knitr (>= 1.28), rmarkdown (>= 2.1), testthat (>= 3.0.0), tibble (>= 3.0.4), xml2 (>= 1.3.2)
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2021-05-04 01:41:47 UTC; c240390
Author: William Michael Landau [aut, cre] (<https://orcid.org/0000-0003-1878-3253>), Samantha Oliver [rev] (<https://orcid.org/0000-0001-5668-1165>), Tristan Mahr [rev] (<https://orcid.org/0000-0002-8890-5116>), Eli Lilly and Company [cph]
Maintainer: William Michael Landau <will.landau@gmail.com>
Repository: CRAN
Date/Publication: 2021-05-11 07:20:02 UTC

More information about tarchetypes at CRAN
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Package InSilicoVA updated to version 1.3.1 with previous version 1.3.0 dated 2020-06-30

Title: Probabilistic Verbal Autopsy Coding with 'InSilicoVA' Algorithm
Description: Computes individual causes of death and population cause-specific mortality fractions using the 'InSilicoVA' algorithm from McCormick et al. (2016) <DOI:10.1080/01621459.2016.1152191>. It uses data derived from verbal autopsy (VA) interviews, in a format similar to the input of the widely used 'InterVA4' method. This package provides general model fitting and customization for 'InSilicoVA' algorithm and basic graphical visualization of the output.
Author: Zehang Richard Li, Tyler McCormick, Sam Clark
Maintainer: Zehang Richard Li <lizehang@gmail.com>

Diff between InSilicoVA versions 1.3.0 dated 2020-06-30 and 1.3.1 dated 2021-05-11

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 InSilicoVA-1.3.1/InSilicoVA/man/stackplot.Rd              |   36 +++++--
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 30 files changed, 361 insertions(+), 191 deletions(-)

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Package fmsb updated to version 0.7.1 with previous version 0.7.0 dated 2019-12-15

Title: Functions for Medical Statistics Book with some Demographic Data
Description: Several utility functions for the book entitled "Practices of Medical and Health Data Analysis using R" (Pearson Education Japan, 2007) with Japanese demographic data and some demographic analysis related functions.
Author: Minato Nakazawa <minato-nakazawa@umin.net>
Maintainer: Minato Nakazawa <minato-nakazawa@umin.net>

Diff between fmsb versions 0.7.0 dated 2019-12-15 and 0.7.1 dated 2021-05-11

 DESCRIPTION             |    8 +++----
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Permanent link

New package ennet with initial version 0.2.2
Package: ennet
Title: Utilities to Extract and Analyse Text Data from the Emergency Nutrition Network Forum
Version: 0.2.2
Authors@R: person(given = "Ernest", family = "Guevarra", email = "ernest@guevarra.io", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-4887-4415"))
Description: The Emergency Nutrition Network or en-net forum is the go to online forum for field practitioners requiring prompt technical advice for operational challenges for which answers are not readily accessible in current guidelines. The questions and the corresponding answers raised within en-net can provide insight into what the key topics of discussion are within the nutrition sector. This package provides utility functions for the extraction, processing and analysis of text data from the online forum.
License: GPL-3
Depends: R (>= 2.10)
Imports: magrittr, rvest, xml2, tibble, dplyr, stringr, lubridate, utils, tidyr
Suggests: knitr, rmarkdown, testthat, spelling
Encoding: UTF-8
Language: en-GB
LazyData: true
URL: https://katilingban.io/ennet/, https://github.com/katilingban/ennet
BugReports: https://github.com/katilingban/ennet/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-05-09 16:46:54 UTC; ernestguevarra
Author: Ernest Guevarra [aut, cre] (<https://orcid.org/0000-0002-4887-4415>)
Maintainer: Ernest Guevarra <ernest@guevarra.io>
Repository: CRAN
Date/Publication: 2021-05-11 07:30:02 UTC

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Package bio3d updated to version 2.4-2 with previous version 2.4-1 dated 2020-01-21

Title: Biological Structure Analysis
Description: Utilities to process, organize and explore protein structure, sequence and dynamics data. Features include the ability to read and write structure, sequence and dynamic trajectory data, perform sequence and structure database searches, data summaries, atom selection, alignment, superposition, rigid core identification, clustering, torsion analysis, distance matrix analysis, structure and sequence conservation analysis, normal mode analysis, principal component analysis of heterogeneous structure data, and correlation network analysis from normal mode and molecular dynamics data. In addition, various utility functions are provided to enable the statistical and graphical power of the R environment to work with biological sequence and structural data. Please refer to the URLs below for more information.
Author: Barry Grant [aut, cre], Xin-Qiu Yao [aut], Lars Skjaerven [aut], Julien Ide [aut]
Maintainer: Barry Grant <bjgrant@ucsd.edu>

Diff between bio3d versions 2.4-1 dated 2020-01-21 and 2.4-2 dated 2021-05-11

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Package spreadr updated to version 0.2.0 with previous version 0.1.0 dated 2018-11-19

Title: Simulating Spreading Activation in a Network
Description: The notion of spreading activation is a prevalent metaphor in the cognitive sciences. This package provides the tools for cognitive scientists and psychologists to conduct computer simulations that implement spreading activation in a network representation. The algorithmic method implemented in 'spreadr' subroutines follows the approach described in Vitevitch, Ercal, and Adagarla (2011, Frontiers), who viewed activation as a fixed cognitive resource that could spread among nodes that were connected to each other via edges or connections (i.e., a network). See Vitevitch, M. S., Ercal, G., & Adagarla, B. (2011). Simulating retrieval from a highly clustered network: Implications for spoken word recognition. Frontiers in Psychology, 2, 369. <doi:10.3389/fpsyg.2011.00369> and Siew, C. S. Q. (2019). spreadr: A R package to simulate spreading activation in a network. Behavior Research Methods, 51, 910-929. <doi: 10.3758/s13428-018-1186-5>.
Author: Cynthia Siew [aut, cre], Dirk U. Wulff [ctb], Ning Yuan Lee [ctb]
Maintainer: Cynthia Siew <cynsiewsq@gmail.com>

Diff between spreadr versions 0.1.0 dated 2018-11-19 and 0.2.0 dated 2021-05-11

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Package maic updated to version 0.1.3 with previous version 0.1.2 dated 2020-04-30

Title: Matching-Adjusted Indirect Comparison
Description: A generalised workflow for generation of subject weights to be used in Matching-Adjusted Indirect Comparison (MAIC) per Signorovitch et al (2012) <doi:10.1016/j.jval.2012.05.004>, Signorovitch et al (2010) <doi:10.2165/11538370-000000000-00000>. In MAIC, unbiased comparison between outcomes of two trials is facilitated by weighting the subject-level outcomes of one trial with weights derived such that the weighted aggregate measures of the prognostic or effect modifying variables are equal to those of the sample in the comparator trial. The functions and classes included in this package wrap and abstract the process demonstrated in the UK National Institute for Health and Care Excellence Decision Support Unit (NICE DSU)'s example (Phillippo et al, (2016) [see URL]), providing a repeatable and easily specifiable workflow for producing multiple comparison variable sets against a variety of target studies, with preprocessing for a number of aggregate target forms (e.g. mean, median, domain limits).
Author: Rob Young [aut, cre]
Maintainer: Rob Young <rob.young@heor.co.uk>

Diff between maic versions 0.1.2 dated 2020-04-30 and 0.1.3 dated 2021-05-11

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Package viridis updated to version 0.6.1 with previous version 0.6.0 dated 2021-04-15

Title: Colorblind-Friendly Color Maps for R
Description: Color maps designed to improve graph readability for readers with common forms of color blindness and/or color vision deficiency. The color maps are also perceptually-uniform, both in regular form and also when converted to black-and-white for printing. This package also contains 'ggplot2' bindings for discrete and continuous color and fill scales. A lean version of the package called 'viridisLite' that does not include the 'ggplot2' bindings can be found at <https://cran.r-project.org/package=viridisLite>.
Author: Simon Garnier [aut, cre], Noam Ross [ctb, cph], Bob Rudis [ctb, cph], Marco Sciaini [ctb, cph], Antônio Pedro Camargo [ctb, cph], Cédric Scherer [ctb, cph]
Maintainer: Simon Garnier <garnier@njit.edu>

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Package RxODE updated to version 1.0.9 with previous version 1.0.8 dated 2021-04-10

Title: Facilities for Simulating from ODE-Based Models
Description: Facilities for running simulations from ordinary differential equation ('ODE') models, such as pharmacometrics and other compartmental models. A compilation manager translates the ODE model into C, compiles it, and dynamically loads the object code into R for improved computational efficiency. An event table object facilitates the specification of complex dosing regimens (optional) and sampling schedules. NB: The use of this package requires both C and Fortran compilers, for details on their use with R please see Section 6.3, Appendix A, and Appendix D in the "R Administration and Installation" manual. Also the code is mostly released under GPL. The 'VODE' and 'LSODA' are in the public domain. The information is available in the inst/COPYRIGHTS.
Author: Matthew L. Fidler [aut] (<https://orcid.org/0000-0001-8538-6691>), Melissa Hallow [aut], Wenping Wang [aut, cre], Zufar Mulyukov [ctb], Alan Hindmarsh [ctb], Awad H. Al-Mohy [ctb], Matt Dowle [ctb], Cleve Moler [ctb], David Cooley [ctb], Drew Schmidt [ctb], Arun Srinivasan [ctb], Ernst Hairer [ctb], Gerhard Wanner [ctb], Goro Fuji [ctb], Hadley Wickham [ctb], Jack Dongarra [ctb], Linda Petzold [ctb], Martin Maechler [ctb], Matteo Fasiolo [ctb], Morwenn [ctb], Nicholas J. Higham [ctb], Roger B. Sidje [ctb], Simon Frost [ctb], Kevin Ushey [ctb], Yu Feng [ctb]
Maintainer: Wenping Wang <wwang8198@gmail.com>

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Package ggplotify updated to version 0.0.7 with previous version 0.0.6 dated 2021-04-22

Title: Convert Plot to 'grob' or 'ggplot' Object
Description: Convert plot function call (using expression or formula) to 'grob' or 'ggplot' object that compatible to the 'grid' and 'ggplot2' ecosystem. With this package, we are able to e.g. using 'cowplot' to align plots produced by 'base' graphics, 'ComplexHeatmap', 'eulerr', 'grid', 'lattice', 'magick', 'pheatmap', 'vcd' etc. by converting them to 'ggplot' objects.
Author: Guangchuang Yu [aut, cre] (<https://orcid.org/0000-0002-6485-8781>)
Maintainer: Guangchuang Yu <guangchuangyu@gmail.com>

Diff between ggplotify versions 0.0.6 dated 2021-04-22 and 0.0.7 dated 2021-05-11

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Package brranching updated to version 0.7.0 with previous version 0.6.0 dated 2020-06-12

Title: Fetch 'Phylogenies' from Many Sources
Description: Includes methods for fetching 'phylogenies' from a variety of sources, including the 'Phylomatic' web service (<http://phylodiversity.net/phylomatic/>), and 'Phylocom' (<https://github.com/phylocom/phylocom/>).
Author: Scott Chamberlain [aut, cre] (<https://orcid.org/0000-0003-1444-9135>)
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

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Package bold updated to version 1.2.0 with previous version 1.1.0 dated 2020-06-17

Title: Interface to Bold Systems API
Description: A programmatic interface to the Web Service methods provided by Bold Systems (<http://www.boldsystems.org/>) for genetic 'barcode' data. Functions include methods for searching by sequences by taxonomic names, ids, collectors, and institutions; as well as a function for searching for specimens, and downloading trace files.
Author: Scott Chamberlain [aut, cre] (<https://orcid.org/0000-0003-1444-9135>)
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

Diff between bold versions 1.1.0 dated 2020-06-17 and 1.2.0 dated 2021-05-11

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Package netdiffuseR (with last version 1.22.0) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2020-05-07 1.22.0

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Package rTLS (with last version 0.2.3.3) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2021-04-26 0.2.3.3

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Package wpa updated to version 1.5.0 with previous version 1.4.3 dated 2021-04-06

Title: Tools for Analysing and Visualising Workplace Analytics Data
Description: Opinionated functions that enable easier and faster analysis of Workplace Analytics data. There are three main types of functions in 'wpa': (i) Standard functions create a 'ggplot' visual or a summary table based on a specific Workplace Analytics metric; (2) Report Generation functions generate HTML reports on a specific analysis area, e.g. Collaboration; (3) Other miscellaneous functions cover more specific applications (e.g. Subject Line text mining) of Workplace Analytics data. This package adheres to 'tidyverse' principles and works well with the pipe syntax. 'wpa' is built with the beginner-to-intermediate R users in mind, and is optimised for simplicity.
Author: Martin Chan [aut, cre], Carlos Morales [aut], Mark Powers [ctb], Ainize Cidoncha [ctb], Rosamary Ochoa Vargas [ctb], Tannaz Sattari [ctb], Lucas Hogner [ctb], Jasminder Thind [ctb], Simone Liebal [ctb], Ellen Trinklein [ctb], Microsoft Corporation [cph]
Maintainer: Martin Chan <martin.chan@microsoft.com>

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 wpa-1.5.0/wpa/man/afterhours_rank.Rd           |    1 
 wpa-1.5.0/wpa/man/afterhours_summary.Rd        |    1 
 wpa-1.5.0/wpa/man/afterhours_trend.Rd          |    4 
 wpa-1.5.0/wpa/man/check_query.Rd               |    4 
 wpa-1.5.0/wpa/man/collaboration_area.Rd        |    1 
 wpa-1.5.0/wpa/man/collaboration_dist.Rd        |    1 
 wpa-1.5.0/wpa/man/collaboration_fizz.Rd        |    1 
 wpa-1.5.0/wpa/man/collaboration_line.Rd        |    1 
 wpa-1.5.0/wpa/man/collaboration_rank.Rd        |    5 
 wpa-1.5.0/wpa/man/collaboration_sum.Rd         |    1 
 wpa-1.5.0/wpa/man/collaboration_trend.Rd       |    4 
 wpa-1.5.0/wpa/man/create_bar.Rd                |   24 +
 wpa-1.5.0/wpa/man/create_bar_asis.Rd           |    1 
 wpa-1.5.0/wpa/man/create_boxplot.Rd            |    1 
 wpa-1.5.0/wpa/man/create_bubble.Rd             |    1 
 wpa-1.5.0/wpa/man/create_dist.Rd               |   40 +++
 wpa-1.5.0/wpa/man/create_fizz.Rd               |    1 
 wpa-1.5.0/wpa/man/create_line.Rd               |    1 
 wpa-1.5.0/wpa/man/create_line_asis.Rd          |    1 
 wpa-1.5.0/wpa/man/create_period_scatter.Rd     |    1 
 wpa-1.5.0/wpa/man/create_rank.Rd               |    8 
 wpa-1.5.0/wpa/man/create_sankey.Rd             |    1 
 wpa-1.5.0/wpa/man/create_scatter.Rd            |    1 
 wpa-1.5.0/wpa/man/create_stacked.Rd            |   22 +
 wpa-1.5.0/wpa/man/create_trend.Rd              |   10 
 wpa-1.5.0/wpa/man/cut_hour.Rd                  |    8 
 wpa-1.5.0/wpa/man/email_dist.Rd                |    1 
 wpa-1.5.0/wpa/man/email_fizz.Rd                |    1 
 wpa-1.5.0/wpa/man/email_line.Rd                |    1 
 wpa-1.5.0/wpa/man/email_rank.Rd                |    1 
 wpa-1.5.0/wpa/man/email_summary.Rd             |    1 
 wpa-1.5.0/wpa/man/email_trend.Rd               |    4 
 wpa-1.5.0/wpa/man/export.Rd                    |    3 
 wpa-1.5.0/wpa/man/external_network_plot.Rd     |    1 
 wpa-1.5.0/wpa/man/extract_hr.Rd                |    1 
 wpa-1.5.0/wpa/man/flag_ch_ratio.Rd             |    3 
 wpa-1.5.0/wpa/man/flag_em_ratio.Rd             |    1 
 wpa-1.5.0/wpa/man/flag_extreme.Rd              |    1 
 wpa-1.5.0/wpa/man/flag_outlooktime.Rd          |    1 
 wpa-1.5.0/wpa/man/flex_index.Rd                |    7 
 wpa-1.5.0/wpa/man/generate_report.Rd           |    3 
 wpa-1.5.0/wpa/man/hr_trend.Rd                  |    2 
 wpa-1.5.0/wpa/man/hrvar_count.Rd               |    2 
 wpa-1.5.0/wpa/man/hrvar_count_all.Rd           |    3 
 wpa-1.5.0/wpa/man/hrvar_trend.Rd               |only
 wpa-1.5.0/wpa/man/identify_churn.Rd            |    1 
 wpa-1.5.0/wpa/man/identify_holidayweeks.Rd     |    1 
 wpa-1.5.0/wpa/man/identify_inactiveweeks.Rd    |    1 
 wpa-1.5.0/wpa/man/identify_nkw.Rd              |   15 -
 wpa-1.5.0/wpa/man/identify_outlier.Rd          |    1 
 wpa-1.5.0/wpa/man/identify_privacythreshold.Rd |    1 
 wpa-1.5.0/wpa/man/identify_query.Rd            |    1 
 wpa-1.5.0/wpa/man/identify_shifts.Rd           |    1 
 wpa-1.5.0/wpa/man/identify_shifts_wp.Rd        |    1 
 wpa-1.5.0/wpa/man/identify_tenure.Rd           |    1 
 wpa-1.5.0/wpa/man/internal_network_plot.Rd     |    1 
 wpa-1.5.0/wpa/man/keymetrics_scan.Rd           |    1 
 wpa-1.5.0/wpa/man/meeting_dist.Rd              |    1 
 wpa-1.5.0/wpa/man/meeting_fizz.Rd              |    1 
 wpa-1.5.0/wpa/man/meeting_line.Rd              |    1 
 wpa-1.5.0/wpa/man/meeting_quality.Rd           |    1 
 wpa-1.5.0/wpa/man/meeting_rank.Rd              |    1 
 wpa-1.5.0/wpa/man/meeting_summary.Rd           |    1 
 wpa-1.5.0/wpa/man/meeting_trend.Rd             |    4 
 wpa-1.5.0/wpa/man/meetingtype_dist.Rd          |    1 
 wpa-1.5.0/wpa/man/meetingtype_dist_ca.Rd       |    5 
 wpa-1.5.0/wpa/man/meetingtype_dist_mt.Rd       |    5 
 wpa-1.5.0/wpa/man/meetingtype_summary.Rd       |    1 
 wpa-1.5.0/wpa/man/mgrcoatt_dist.Rd             |    1 
 wpa-1.5.0/wpa/man/mgrrel_matrix.Rd             |    4 
 wpa-1.5.0/wpa/man/one2one_dist.Rd              |    1 
 wpa-1.5.0/wpa/man/one2one_fizz.Rd              |    1 
 wpa-1.5.0/wpa/man/one2one_freq.Rd              |   25 +-
 wpa-1.5.0/wpa/man/one2one_line.Rd              |    1 
 wpa-1.5.0/wpa/man/one2one_rank.Rd              |    1 
 wpa-1.5.0/wpa/man/one2one_sum.Rd               |    1 
 wpa-1.5.0/wpa/man/one2one_trend.Rd             |    4 
 wpa-1.5.0/wpa/man/p_test.Rd                    |    3 
 wpa-1.5.0/wpa/man/period_change.Rd             |    4 
 wpa-1.5.0/wpa/man/personas_hclust.Rd           |    3 
 wpa-1.5.0/wpa/man/remove_outliers.Rd           |    4 
 wpa-1.5.0/wpa/man/standardise_pq.Rd            |    1 
 wpa-1.5.0/wpa/man/subject_validate.Rd          |    1 
 wpa-1.5.0/wpa/man/subject_validate_report.Rd   |    1 
 wpa-1.5.0/wpa/man/tm_cooc.Rd                   |    5 
 wpa-1.5.0/wpa/man/track_HR_change.Rd           |    6 
 wpa-1.5.0/wpa/man/validation_report.Rd         |    1 
 wpa-1.5.0/wpa/man/workloads_dist.Rd            |    1 
 wpa-1.5.0/wpa/man/workloads_fizz.Rd            |    1 
 wpa-1.5.0/wpa/man/workloads_line.Rd            |    1 
 wpa-1.5.0/wpa/man/workloads_rank.Rd            |    1 
 wpa-1.5.0/wpa/man/workloads_summary.Rd         |    1 
 wpa-1.5.0/wpa/man/workloads_trend.Rd           |    4 
 wpa-1.5.0/wpa/man/workpatterns_area.Rd         |    1 
 wpa-1.5.0/wpa/man/workpatterns_classify.Rd     |   84 +++++-
 wpa-1.5.0/wpa/man/workpatterns_classify_bw.Rd  |  185 ++++++++-------
 wpa-1.5.0/wpa/man/workpatterns_classify_pav.Rd |  163 ++++++-------
 wpa-1.5.0/wpa/man/workpatterns_rank.Rd         |    1 
 wpa-1.5.0/wpa/vignettes/intro-to-wpa.Rmd       |    2 
 153 files changed, 1754 insertions(+), 742 deletions(-)

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Package erah updated to version 1.1.2 with previous version 1.1.1 dated 2020-07-06

Title: Automated Spectral Deconvolution, Alignment, and Metabolite Identification in GC/MS-Based Untargeted Metabolomics
Description: Automated compound deconvolution, alignment across samples, and identification of metabolites by spectral library matching in Gas Chromatography - Mass spectrometry (GC-MS) untargeted metabolomics. Outputs a table with compound names, matching scores and the integrated area of the compound for each sample. Package implementation is described in Domingo-Almenara et al. (2016) <doi:10.1021/acs.analchem.6b02927>.
Author: Xavier Domingo-Almenara [aut, cre, cph], Jasen P. Finch [ctb], Sara Samino [aut], Maria Vinaixa [aut], Alexandre Perera [aut, ths], Jesus Brezmes [aut, ths], Oscar Yanes [aut, ths]
Maintainer: Xavier Domingo-Almenara <xavier.domingoa@eurecat.org>

Diff between erah versions 1.1.1 dated 2020-07-06 and 1.1.2 dated 2021-05-11

 DESCRIPTION             |   10 +++++-----
 MD5                     |    8 ++++----
 R/zzz.R                 |   28 ++++++----------------------
 inst/NEWS               |    4 ++++
 inst/doc/eRahManual.pdf |binary
 5 files changed, 19 insertions(+), 31 deletions(-)

More information about erah at CRAN
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